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The delicate tuning of digit forces to object properties can be disrupted by a number of neurological and musculoskeletal diseases. One such condition is Carpal Tunnel Syndrome (CTS), a compression neuropathy of the median nerve that causes sensory and motor deficits in a subset of digits in the hand. Whereas the effects of CTS on median nerve physiology are well understood, the extent to which it affects whole-hand manipulation remains to be addressed. CTS affects only the lateral three and a half digits, which raises the question of how the central nervous system integrates sensory feedback from affected and unaffected digits to plan and execute whole-hand object manipulation. We addressed this question by asking CTS patients and healthy controls to grasp, lift, and hold a grip device (445, 545, or 745 g) for several consecutive trials. We found that CTS patients were able to successfully adapt grip force to object weight. However, multi-digit force coordination in patients was characterized by lower discrimination of force modulation to lighter object weights, higher across-trial digit force variability, the consistent use of excessively large digit forces across consecutive trials, and a lower ability to minimize net moments on the object. Importantly, the mechanical requirement of attaining equilibrium of forces and torques caused CTS patients to exert excessive forces at both CTS-affected digits and digits with intact sensorimotor capabilities. These findings suggest that CTS-induced deficits in tactile sensitivity interfere with the formation of accurate sensorimotor memories of previous manipulations. Consequently, CTS patients use compensatory strategies to maximize grasp stability at the expense of exerting consistently larger multi-digit forces than controls. These behavioral deficits might be particularly detrimental for tasks that require fine regulation of fingertip forces for manipulating light or fragile objects.

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Fingertip forces result from activation of muscles that cross the wrist and muscles whose origins and insertions reside within the hand (extrinsic and intrinsic hand muscles, respectively). Thus, tasks that involve changes in wrist angle affect the moment arm and length, hence the force-producing capabilities, of extrinsic muscles only. If a grasping task requires the exertion of constant fingertip forces, the Central Nervous System (CNS) may respond to changes in wrist angle by modulating the neural drive to extrinsic or intrinsic muscles only or by co-activating both sets of muscles. To distinguish between these scenarios, we recorded electromyographic (EMG) activity of intrinsic and extrinsic muscles of the thumb and index finger as a function of wrist angle during a two-digit object hold task. We hypothesized that changes in wrist angle would elicit EMG amplitude modulation of the extrinsic and intrinsic hand muscles. In one experimental condition we asked subjects to exert the same digit forces at each wrist angle, whereas in a second condition subjects could choose digit forces for holding the object. EMG activity was significantly modulated in both extrinsic and intrinsic muscles as a function of wrist angle (both p < 0.05) but only for the constant force condition. Furthermore, EMG modulation resulted from uniform scaling of EMG amplitude across all muscles. We conclude that the CNS controlled both extrinsic and intrinsic muscles as a muscle synergy. These findings are discussed within the theoretical frameworks of synergies and common neural input across motor nuclei of hand muscles.

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. Musclepair specific distribution and grip-type modulation of neural common input to extrinsic digit flexors. J Neurophysiol 96: 1258 -1266, 2006. First published May 24, 2006 doi:10.1152/jn.00327.2006. To gain insight into the synergistic control of hand muscles, we have recently quantified the strength of correlated neural activity across motor units from extrinsic digit flexors during a five-digit object-hold task. We found stronger synchrony and coherence across motor units from thumb and index finger flexor muscle compartment than between the thumb flexor and other finger flexor muscle compartments. The present study of two-digit object hold was designed to determine the extent to which such distribution of common input among thumbfinger flexor muscle compartments, revealed by holding an object with five digits, is preserved when varying the functional role of a given digit pair. We recorded normal force exerted by the digits and electrical activity of single motor units from muscle flexor pollicis longus (FPL) and two compartments of the m. flexor digitorum profundus (FDP2 and FDP3; index and middle finger, respectively). Consistent with our previous results from five-digit grasping, synchrony and coherence across motor units from FPL-FDP2 was significantly stronger than in FPL-FDP3 during object hold with two digits [common input strength: 0.49 Ϯ 0.02 and 0.35 Ϯ 0.02 (means Ϯ SE), respectively; peak coherence: 0.0054 and 0.0038, respectively]. This suggests that the distribution of common neural input is muscle-pair specific regardless of grip type. However, the strength of coherence, but not synchrony, was significantly stronger in two-versus five-digit object hold for both muscle combinations, suggesting the periodicity of common input is sensitive to grip type.

We recently examined the extent to which motor units of digit flexor muscles receive common input during multidigit grasping. This task elicited moderate to strong motor-unit synchrony (common input strength, CIS) across muscles (flexor digitorum profundus, FDP, and flexor pollicis longus, FPL) and across FDP muscle compartments, although the strength of this common input was not uniform across digit pairs. To further characterize the neural mechanisms underlying the control of multidigit grasping, we analyzed the relationship between firing of single motor units from these hand muscles in the frequency domain by computing coherence. We report three primary findings. First, in contrast to what has been reported in intrinsic hand muscles, motor units belonging to different muscles and muscle compartments of extrinsic digit flexors exhibited significant coherence in the 0- to 5- and 5- to 10-Hz frequency ranges and much weaker coherence in the higher 10–20 Hz range (maximum 0.0025 and 0.0008, respectively, pooled across all FDP compartment pairs). Second, the strength and incidence of coherence differed considerably across digit pairs. Third, contrary to what has been reported in the literature, across-muscle coherence can be stronger and more prevalent than within-muscle coherence, as FPL–FDP2 (thumb-index digit pair) exhibited the strongest and most prevalent coherence in our data (0.010 and 43% at 3 Hz, respectively). The heterogeneous organization of common input to these muscles and muscle compartments is discussed in relation to the functional role of individual digit pairs in the coordination of multiple digit forces in grasping.

In the past two decades a large number of studies have successfully characterized important features of the kinetics and kinematics of object grasping and manipulation, providing significant insight into how the Central Nervous System (CNS) controls the hand, one of the most complex motor systems, in a variety of behaviors. In this chapter we briefly review studies of hand kinematics and kinetics and highlight their major findings and open questions. The major focus of this chapter is on the neural control of the hand, an objective that has been pursued by studies on electromyography (EMG) of hand muscles. Here we review what has been learned through different yet complementary methodological approaches. In particular, the study of single motor unit activity has revealed how the distribution of common neural input within and across hand muscles might reflect a muscle-pair specific organization. Studies of motor unit population have revealed important synergistic patterns of muscle activity while also revealing muscle-pair specific patterns of neural coupling. We conclude the chapter with the results of recent simulation studies aiming at combining advantages of single and multi-unit recordings to maximize the amount of information that can be extracted from EMG signal analysis.